3 papers
stat.ML2026
Generative Modeling of Discrete Data Using Geometric Latent Subspaces
Daniel Gonzalez-Alvarado, Jonas Cassel, Stefania Petra +1
We propose a geometric latent-subspace framework for generative modeling of discrete data. Specifically, we introduce latent subspaces in the exponential parameter space of product…
cs.CV2025
Riemannian Patch Assignment Gradient Flows
Daniel Gonzalez-Alvarado, Fabio Schlindwein, Jonas Cassel +3
This paper introduces patch assignment flows for metric data labeling on graphs. Labelings are determined by regularizing initial local labelings through the dynamic interaction of…
stat.ML2025
Generative Assignment Flows for Representing and Learning Joint Distributions of Discrete Data
Bastian Boll, Daniel Gonzalez-Alvarado, Stefania Petra +1
We introduce a novel generative model for the representation of joint probability distributions of a possibly large number of discrete random variables. The approach uses measure t…